Yijun Yuan (元祎君)

CV | ResearchGate | codes

News

  • PhD research visiting in Prof. Marc Pollefeys’s group in ETH Zürich (Jan, 2024)

  • Uni-Fusion: Universal Continuous Mapping” was accepted to T-RO 2024 (December, 2023)

  • Online Learning of Neural Surface Light Fields alongside Real-time Incremental 3D Reconstruction” was accepted to RAL 2023 (April, 2023)

  • An Algorithm for the SE(3)-Transformation on Neural Implicit Maps for Remapping Functions” was accepted to RAL 2022 (June, 2022)

  • Indirect Point Cloud Registration: Aligning Distance Fields using a Pseudo Third Point Set” was accepted to RAL 2022 (May, 2022)

  • A new start in Wuerzburg University (15 sept, 2021. )


Recent researches

SceneFactory: A Workflow-centric and Unified Framework for Incremental Scene Modeling
Yijun Yuan, Michael Bleier, Andreas Nuchter
paper | website

Following the structure of a “Factory”, we introduce workflow-centric framework that provides “assembly lines” for a wide range of applications, to achieve high flexibility, adaptability and production diversification.

Uni-Fusion: Universal Continuous Mapping
Yijun Yuan, Andreas Nuchter
IEEE Transactions on Robotics (T-RO), 2024
website | paper | code

The first universal continuous mapping framework for surfaces, surface properties (color, infrared, style, saliency, etc.) and more (latent features in CLIP embedding space, etc.).

Online Learning of Neural Surface Light Fields alongside Real-time Incremental 3D Reconstruction
Yijun Yuan, Andreas Nuchter
IEEE Robotics and Automation Letters (RAL), 2023
website | paper | code

NSLF-OL explores more fully decoupling the representation of geometry and color. Working alongside real-time surface reconstruction, NSLF-OL focuses on surface field to provide efficient online modeling of light.

An Algorithm for the SE(3)-Transformation on Neural Implicit Maps for Remapping Functions
Yijun Yuan, Andreas Nuchter
IEEE Robotics and Automation Letters (RAL), 2022
website | paper | code

SE(3)-transformation on neural-implicit maps and enable remapping function. This is the first algorithm that make neural-implicit based reconstruction compatible with Loop-closure.

Indirect Point Cloud Registration: Aligning Distance Fields using a Pseudo Third Point Set
Yijun Yuan, Andreas Nuchter
IEEE Robotics and Automation Letters (RAL), 2022
paper | code

Registration two point cloud with a pseudo-third point set. Thus method have potential to work with neural-implicit registration.


Full publications show in page. All codes have been open-released.